def get_hole_stats(self, image, coord, radius):
## select the region of interest
rmin = int(coord[0] - radius)
rmax = int(coord[0] + radius)
cmin = int(coord[1] - radius)
cmax = int(coord[1] + radius)
## beware of boundaries
if rmin < 0 or rmax >= image.shape[
0] or cmin < 0 or cmax > image.shape[1]:
return None
subimage = image[rmin:rmax + 1, cmin:cmax + 1]
if self.save_mrc:
mrc.write(subimage, 'hole.mrc')
center = subimage.shape[0] / 2.0, subimage.shape[1] / 2.0
mask = self.circle.get(subimage.shape, center, 0, radius)
if self.save_mrc:
mrc.write(mask, 'holemask.mrc')
im = numpy.ravel(subimage)
mask = numpy.ravel(mask)
roi = numpy.compress(mask, im)
mean = arraystats.mean(roi)
std = arraystats.std(roi)
n = len(roi)
return {'mean': mean, 'std': std, 'n': n}
def setStatistics(self, array=None, statistics={}):
try:
mean = statistics['mean']
except KeyError:
if array is None:
mean = None
else:
mean = arraystats.mean(array)
try:
min = statistics['min']
except KeyError:
if array is None:
min = None
else:
min = arraystats.min(array)
try:
max = statistics['max']
except KeyError:
if array is None:
max = None
else:
max = arraystats.max(array)
try:
sd = statistics['stdev']
except KeyError:
if array is None:
sd = None
else:
sd = arraystats.std(array)
if mean is None:
meanstr = ''
else:
meanstr = '%g' % mean
if min is None:
minstr = ''
else:
minstr = '%g' % min
if max is None:
maxstr = ''
else:
maxstr = '%g' % max
if sd is None:
sdstr = ''
else:
sdstr = '%g' % sd
self.meanlabel.SetLabel(meanstr)
self.minlabel.SetLabel(minstr)
self.maxlabel.SetLabel(maxstr)
self.sdlabel.SetLabel(sdstr)
self.sizer.Layout()
def setStatistics(self, array=None, statistics={}):
try:
mean = statistics['mean']
except KeyError:
if array is None:
mean = None
else:
mean = arraystats.mean(array)
try:
min = statistics['min']
except KeyError:
if array is None:
min = None
else:
min = arraystats.min(array)
try:
max = statistics['max']
except KeyError:
if array is None:
max = None
else:
max = arraystats.max(array)
try:
sd = statistics['stdev']
except KeyError:
if array is None:
sd = None
else:
sd = arraystats.std(array)
if mean is None:
meanstr = ''
else:
meanstr = '%g' % mean
if min is None:
minstr = ''
else:
minstr = '%g' % min
if max is None:
maxstr = ''
else:
maxstr = '%g' % max
if sd is None:
sdstr = ''
else:
sdstr = '%g' % sd
self.meanlabel.SetLabel(meanstr)
self.minlabel.SetLabel(minstr)
self.maxlabel.SetLabel(maxstr)
self.sdlabel.SetLabel(sdstr)
self.sizer.Layout()
def threshold_correlation(self, threshold=None):
'''
Threshold the correlation image.
'''
if self.__results['correlation'] is None:
raise RuntimeError('need correlation image to threshold')
self.configure_threshold(threshold)
cc = self.__results['correlation']
mean = arraystats.mean(cc)
std = arraystats.std(cc)
thresh = mean + self.threshold * std
t = imagefun.threshold(cc, thresh)
self.__update_result('threshold', t)
if self.save_mrc:
mrc.write(t, 'threshold.mrc')
def get_box_stats(self, image, coord, boxsize):
## select the region of interest
b2 = boxsize / 2
rmin = int(coord[1]-b2)
rmax = int(coord[1]+b2)
cmin = int(coord[0]-b2)
cmax = int(coord[0]+b2)
## beware of boundaries
if rmin < 0: rmin = 0
if rmax >= image.shape[0]: rmax = image.shape[0]-1
if cmin < 0: cmin = 0
if cmax >= image.shape[1]: cmax = image.shape[1]-1
subimage = image[rmin:rmax+1, cmin:cmax+1]
roi = numpy.ravel(subimage)
mean = arraystats.mean(roi)
std = arraystats.std(roi)
n = len(roi)
stats = {'mean':mean, 'std': std, 'n':n}
return stats
def get_box_stats(self, image, coord, boxsize):
## select the region of interest
b2 = boxsize / 2
rmin = int(coord[1] - b2)
rmax = int(coord[1] + b2)
cmin = int(coord[0] - b2)
cmax = int(coord[0] + b2)
## beware of boundaries
if rmin < 0: rmin = 0
if rmax >= image.shape[0]: rmax = image.shape[0] - 1
if cmin < 0: cmin = 0
if cmax >= image.shape[1]: cmax = image.shape[1] - 1
subimage = image[rmin:rmax + 1, cmin:cmax + 1]
roi = numpy.ravel(subimage)
mean = arraystats.mean(roi)
std = arraystats.std(roi)
n = len(roi)
stats = {'mean': mean, 'std': std, 'n': n}
return stats
def get_hole_stats(self, image, coord, radius):
## select the region of interest
rmin = int(coord[0]-radius)
rmax = int(coord[0]+radius)
cmin = int(coord[1]-radius)
cmax = int(coord[1]+radius)
## beware of boundaries
if rmin < 0 or rmax >= image.shape[0] or cmin < 0 or cmax > image.shape[1]:
return None
subimage = image[rmin:rmax+1, cmin:cmax+1]
save_mrc(subimage, 'hole.mrc')
center = subimage.shape[0]/2.0, subimage.shape[1]/2.0
mask = self.circle.get(subimage.shape, center, 0, radius)
save_mrc(mask, 'holemask.mrc')
im = Numeric.ravel(subimage)
mask = Numeric.ravel(mask)
roi = Numeric.compress(mask, im)
mean = arraystats.mean(roi)
std = arraystats.std(roi)
n = len(roi)
return {'mean':mean, 'std': std, 'n':n}
def calcStats(self, imdata):
stats = {}
stats['mean'] = arraystats.mean(imdata['image'])
stats['stdev'] = arraystats.std(imdata['image'])
return stats
def calcStats(self, imdata):
stats = {}
stats['mean'] = arraystats.mean(imdata['image'])
stats['stdev'] = arraystats.std(imdata['image'])
return stats